Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
机器未来
Paddle
提交
f5fc9c3b
P
Paddle
项目概览
机器未来
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
1
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
1
Issue
1
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
f5fc9c3b
编写于
5月 29, 2018
作者:
Y
Yan Chunwei
提交者:
GitHub
5月 29, 2018
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
feature/mul converter (#10841)
上级
8f7b020b
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
242 addition
and
21 deletion
+242
-21
paddle/fluid/inference/analysis/helper.h
paddle/fluid/inference/analysis/helper.h
+9
-2
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+4
-1
paddle/fluid/inference/tensorrt/convert/mul_op.cc
paddle/fluid/inference/tensorrt/convert/mul_op.cc
+15
-1
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
...le/fluid/inference/tensorrt/convert/test_activation_op.cc
+2
-0
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
+47
-0
paddle/fluid/inference/tensorrt/convert/test_op_converter.cc
paddle/fluid/inference/tensorrt/convert/test_op_converter.cc
+0
-2
paddle/fluid/inference/tensorrt/convert/ut_helper.h
paddle/fluid/inference/tensorrt/convert/ut_helper.h
+156
-0
paddle/fluid/inference/tensorrt/engine.cc
paddle/fluid/inference/tensorrt/engine.cc
+9
-6
paddle/fluid/inference/tensorrt/helper.h
paddle/fluid/inference/tensorrt/helper.h
+0
-9
未找到文件。
paddle/fluid/inference/analysis/helper.h
浏览文件 @
f5fc9c3b
...
...
@@ -24,6 +24,15 @@ namespace paddle {
namespace
inference
{
namespace
analysis
{
template
<
typename
Vec
>
int
AccuDims
(
Vec
&&
vec
,
int
size
)
{
int
res
=
1
;
for
(
int
i
=
0
;
i
<
size
;
i
++
)
{
res
*=
std
::
forward
<
Vec
>
(
vec
)[
i
];
}
return
res
;
}
#define SET_TYPE(type__) dic_[typeid(type__).hash_code()] = #type__;
/*
* Map typeid to representation.
...
...
@@ -101,7 +110,5 @@ class OrderedRegistry {
}
// namespace paddle
#define PADDLE_DISALLOW_COPY_AND_ASSIGN(type__) \
\
type__(const type__ &) = delete; \
\
void operator=(const type__ &) = delete;
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
浏览文件 @
f5fc9c3b
nv_test
(
test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS
${
FLUID_CORE_MODULES
}
)
# Add TRT tests
nv_test
(
test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine
)
# This test is not stable
# See https://paddleci.ngrok.io/viewLog.html?tab=buildLog&buildTypeId=Paddle_PrCi2&buildId=36834&_focus=8828
#nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc io_converter.cc
# DEPS ${FLUID_CORE_MODULES} activation_op tensorrt_engine
# SERIAL)
nv_test
(
test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor
)
nv_test
(
test_trt_mul_op SRCS test_mul_op.cc mul_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine mul_op SERIAL
)
paddle/fluid/inference/tensorrt/convert/mul_op.cc
浏览文件 @
f5fc9c3b
...
...
@@ -18,11 +18,25 @@ namespace paddle {
namespace
inference
{
namespace
tensorrt
{
/*
* MulOp, IMatrixMultiplyLayer in TRT. This Layer doesn't has weights.
*/
class
MulOpConverter
:
public
OpConverter
{
public:
MulOpConverter
()
{}
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
)
override
{
LOG
(
INFO
)
<<
"convert a fluid mul op to tensorrt fc layer without bias"
;
VLOG
(
4
)
<<
"convert a fluid mul op to tensorrt fc layer without bias"
;
framework
::
OpDesc
op_desc
(
op
,
nullptr
,
nullptr
);
// Declare inputs
auto
*
input1
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"X"
)[
0
]);
auto
*
input2
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"Y"
)[
0
]);
// Both the input1 and input2 do not need transpose.
auto
*
layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
MatrixMultiply
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
input1
),
false
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
input2
),
false
);
engine_
->
DeclareOutput
(
layer
,
0
,
op_desc
.
Output
(
"Out"
)[
0
]);
}
};
...
...
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
浏览文件 @
f5fc9c3b
...
...
@@ -102,3 +102,5 @@ TEST(OpConverter, ConvertRelu) {
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
activation
);
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
0 → 100644
浏览文件 @
f5fc9c3b
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <gtest/gtest.h>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
TEST
(
MulOpConverter
,
main
)
{
TRTConvertValidation
validator
(
10
,
1000
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims2
(
10
,
6
));
validator
.
DeclInputVar
(
"mul-Y"
,
nvinfer1
::
Dims2
(
6
,
10
));
validator
.
DeclOutputVar
(
"mul-Out"
,
nvinfer1
::
Dims2
(
10
,
10
));
// Prepare Op description
framework
::
OpDesc
desc
;
desc
.
SetType
(
"mul"
);
desc
.
SetInput
(
"X"
,
{
"mul-X"
});
desc
.
SetInput
(
"Y"
,
{
"mul-Y"
});
desc
.
SetOutput
(
"Out"
,
{
"mul-Out"
});
LOG
(
INFO
)
<<
"set OP"
;
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
10
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
mul
);
paddle/fluid/inference/tensorrt/convert/test_op_converter.cc
浏览文件 @
f5fc9c3b
...
...
@@ -23,8 +23,6 @@ namespace tensorrt {
TEST
(
OpConverter
,
ConvertBlock
)
{
framework
::
ProgramDesc
prog
;
auto
*
block
=
prog
.
MutableBlock
(
0
);
auto
*
mul_op
=
block
->
AppendOp
();
mul_op
->
SetType
(
"mul"
);
auto
*
conv2d_op
=
block
->
AppendOp
();
conv2d_op
->
SetType
(
"conv2d"
);
...
...
paddle/fluid/inference/tensorrt/convert/ut_helper.h
0 → 100644
浏览文件 @
f5fc9c3b
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
/*
* This file implements a UT framework to make the validation of transforming
* Fluid Op to TRT Layer.
*/
#pragma once
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/inference/tensorrt/engine.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
/*
* Get a random float value between [low, high]
*/
float
random
(
float
low
,
float
high
)
{
static
std
::
random_device
rd
;
static
std
::
mt19937
mt
(
rd
());
std
::
uniform_real_distribution
<
double
>
dist
(
1.0
,
10.0
);
return
dist
(
mt
);
}
void
RandomizeTensor
(
framework
::
LoDTensor
*
tensor
,
const
platform
::
Place
&
place
,
const
platform
::
DeviceContext
&
ctx
)
{
auto
dims
=
tensor
->
dims
();
size_t
num_elements
=
analysis
::
AccuDims
(
dims
,
dims
.
size
());
PADDLE_ENFORCE_GT
(
num_elements
,
0
);
auto
*
data
=
tensor
->
mutable_data
<
float
>
(
place
);
for
(
size_t
i
=
0
;
i
<
num_elements
;
i
++
)
{
*
(
data
+
i
)
=
random
(
0.
,
1.
);
}
}
/*
* Help to validate the correctness between Fluid Op and the corresponding TRT
* layer.
*/
class
TRTConvertValidation
{
public:
TRTConvertValidation
()
=
delete
;
TRTConvertValidation
(
int
batch_size
,
int
workspace_size
=
1
<<
10
)
{
// create engine.
engine_
.
reset
(
new
TensorRTEngine
(
10
,
1
<<
10
,
&
stream_
));
engine_
->
InitNetwork
();
PADDLE_ENFORCE_EQ
(
cudaStreamCreate
(
&
stream_
),
0
);
}
// Declare a Variable as input with random initialization.
void
DeclInputVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
DeclVar
(
name
,
dims
);
// Declare TRT inputs.
engine_
->
DeclareInput
(
name
,
nvinfer1
::
DataType
::
kFLOAT
,
dims
);
}
void
DeclOutputVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
DeclVar
(
name
,
dims
);
}
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
// Init Fluid tensor.
std
::
vector
<
int
>
dim_vec
(
dims
.
nbDims
);
for
(
int
i
=
0
;
i
<
dims
.
nbDims
;
i
++
)
{
dim_vec
[
i
]
=
dims
.
d
[
i
];
}
auto
*
x
=
scope_
.
Var
(
name
);
auto
*
x_tensor
=
x
->
GetMutable
<
framework
::
LoDTensor
>
();
x_tensor
->
Resize
(
framework
::
make_ddim
(
dim_vec
));
RandomizeTensor
(
x_tensor
,
place
,
ctx
);
}
void
SetOp
(
const
framework
::
proto
::
OpDesc
&
desc
)
{
op_
=
framework
::
OpRegistry
::
CreateOp
(
desc
);
OpConverter
op_converter
;
op_converter
.
ConvertOp
(
desc
,
engine_
.
get
());
engine_
->
FreezeNetwork
();
// Declare outputs.
op_desc_
.
reset
(
new
framework
::
OpDesc
(
desc
,
nullptr
,
nullptr
));
// Set Inputs.
for
(
const
auto
&
input
:
op_desc_
->
InputArgumentNames
())
{
auto
*
var
=
scope_
.
FindVar
(
input
);
PADDLE_ENFORCE
(
var
);
auto
tensor
=
var
->
GetMutable
<
framework
::
LoDTensor
>
();
engine_
->
SetInputFromCPU
(
input
,
static_cast
<
void
*>
(
tensor
->
data
<
float
>
()),
sizeof
(
float
)
*
analysis
::
AccuDims
(
tensor
->
dims
(),
tensor
->
dims
().
size
()));
}
}
void
Execute
(
int
batch_size
)
{
// Execute Fluid Op
// Execute TRT
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
engine_
->
Execute
(
batch_size
);
op_
->
Run
(
scope_
,
place
);
ASSERT_FALSE
(
op_desc_
->
OutputArgumentNames
().
empty
());
for
(
const
auto
&
output
:
op_desc_
->
OutputArgumentNames
())
{
std
::
vector
<
float
>
fluid_out
;
std
::
vector
<
float
>
trt_out
(
200
);
engine_
->
GetOutputInCPU
(
output
,
&
trt_out
[
0
],
200
*
sizeof
(
float
));
auto
*
var
=
scope_
.
FindVar
(
output
);
auto
tensor
=
var
->
GetMutable
<
framework
::
LoDTensor
>
();
framework
::
TensorToVector
(
*
tensor
,
ctx
,
&
fluid_out
);
// Compare two output
ASSERT_FALSE
(
fluid_out
.
empty
());
for
(
size_t
i
=
0
;
i
<
fluid_out
.
size
();
i
++
)
{
EXPECT_LT
(
std
::
abs
(
fluid_out
[
i
]
-
trt_out
[
i
]),
0.001
);
}
}
}
framework
::
Scope
&
scope
()
{
return
scope_
;
}
private:
std
::
unique_ptr
<
TensorRTEngine
>
engine_
;
cudaStream_t
stream_
;
framework
::
Scope
scope_
;
std
::
unique_ptr
<
framework
::
OperatorBase
>
op_
;
std
::
unique_ptr
<
framework
::
OpDesc
>
op_desc_
;
};
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tensorrt/engine.cc
浏览文件 @
f5fc9c3b
...
...
@@ -18,6 +18,7 @@ limitations under the License. */
#include <cuda.h>
#include <glog/logging.h>
#include <string>
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/inference/tensorrt/helper.h"
#include "paddle/fluid/platform/enforce.h"
...
...
@@ -71,9 +72,10 @@ void TensorRTEngine::FreezeNetwork() {
for
(
auto
&
item
:
buffer_sizes_
)
{
if
(
item
.
second
==
0
)
{
auto
slot_offset
=
infer_engine_
->
getBindingIndex
(
item
.
first
.
c_str
());
auto
dims
=
infer_engine_
->
getBindingDimensions
(
slot_offset
);
item
.
second
=
kDataTypeSize
[
static_cast
<
int
>
(
infer_engine_
->
getBindingDataType
(
slot_offset
))]
*
AccumDims
(
infer_engine_
->
getBindingDimensions
(
slot_offset
)
);
analysis
::
AccuDims
(
dims
.
d
,
dims
.
nbDims
);
}
auto
&
buf
=
buffer
(
item
.
first
);
CHECK
(
buf
.
buffer
==
nullptr
);
// buffer should be allocated only once.
...
...
@@ -85,14 +87,15 @@ void TensorRTEngine::FreezeNetwork() {
nvinfer1
::
ITensor
*
TensorRTEngine
::
DeclareInput
(
const
std
::
string
&
name
,
nvinfer1
::
DataType
dtype
,
const
nvinfer1
::
Dims
&
dim
)
{
const
nvinfer1
::
Dims
&
dim
s
)
{
PADDLE_ENFORCE_EQ
(
0
,
buffer_sizes_
.
count
(
name
),
"duplicate input name %s"
,
name
);
PADDLE_ENFORCE
(
infer_network_
!=
nullptr
,
"should initnetwork first"
);
auto
*
input
=
infer_network_
->
addInput
(
name
.
c_str
(),
dtype
,
dim
);
auto
*
input
=
infer_network_
->
addInput
(
name
.
c_str
(),
dtype
,
dim
s
);
PADDLE_ENFORCE
(
input
,
"infer network add input %s failed"
,
name
);
buffer_sizes_
[
name
]
=
kDataTypeSize
[
static_cast
<
int
>
(
dtype
)]
*
AccumDims
(
dim
);
buffer_sizes_
[
name
]
=
kDataTypeSize
[
static_cast
<
int
>
(
dtype
)]
*
analysis
::
AccuDims
(
dims
.
d
,
dims
.
nbDims
);
TensorRTEngine
::
SetITensor
(
name
,
input
);
return
input
;
}
...
...
@@ -162,13 +165,13 @@ void TensorRTEngine::SetInputFromCPU(const std::string& name, void* data,
void
TensorRTEngine
::
SetITensor
(
const
std
::
string
&
name
,
nvinfer1
::
ITensor
*
tensor
)
{
PADDLE_ENFORCE
(
tensor
!=
nullptr
);
PADDLE_ENFORCE_EQ
(
0
,
itensor_map_
.
count
(
name
),
"duplicate
it
ensor name %s"
,
PADDLE_ENFORCE_EQ
(
0
,
itensor_map_
.
count
(
name
),
"duplicate
IT
ensor name %s"
,
name
);
itensor_map_
[
name
]
=
tensor
;
}
nvinfer1
::
ITensor
*
TensorRTEngine
::
GetITensor
(
const
std
::
string
&
name
)
{
PADDLE_ENFORCE
(
itensor_map_
.
count
(
name
),
"no
it
ensor %s"
,
name
);
PADDLE_ENFORCE
(
itensor_map_
.
count
(
name
),
"no
IT
ensor %s"
,
name
);
return
itensor_map_
[
name
];
}
...
...
paddle/fluid/inference/tensorrt/helper.h
浏览文件 @
f5fc9c3b
...
...
@@ -26,15 +26,6 @@ namespace tensorrt {
namespace
dy
=
paddle
::
platform
::
dynload
;
static
size_t
AccumDims
(
nvinfer1
::
Dims
dims
)
{
size_t
num
=
dims
.
nbDims
==
0
?
0
:
1
;
for
(
int
i
=
0
;
i
<
dims
.
nbDims
;
i
++
)
{
PADDLE_ENFORCE_GT
(
dims
.
d
[
i
],
0
);
num
*=
dims
.
d
[
i
];
}
return
num
;
}
// TensorRT data type to size
const
int
kDataTypeSize
[]
=
{
4
,
// kFLOAT
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录